Data Scientist

We are Qubit

Qubit is the leader in delivering highly persuasive personalization at scale. Leading brands in retail & travel work with Qubit to transform the way they understand and influence their customers. Companies like MandM Direct, Topshop, Louis Vuitton, Ubisoft, River Island and Halfords are using the Qubit personalization platform to increase revenue, build loyalty and significantly improve their marketing efficiency. Every week Qubit is used to personalize approximately $600 million in online sales. Headquartered in London, the company has offices across Europe and the U.S.

Join our community of engineers working with the latest cutting edge technology in a friendly and supportive environment. As a member of our cross functional product engineering team your mission is simple: To use whatever techniques and technology are best for the task in order to solve real problems and ship great products for our customers. You will be given the freedom and autonomy to solve a diverse set of challenges while also being able to influence the direction of what we build. Simply put, we love writing good code that delivers value to the business and our customers. Here is some tech we are particularly interested in at the moment:

• AutoML
• Facebook Prophet
• Scikit learn
• PyMC3
• BigQueryML

• Understand business problems and translate them into data driven solutions
• Keep up with the latest data science techniques and their potential application to AI-led merchandising
• Leverage the right machine learning and statistical techniques to go beyond the bounds of what a human can do, and build products that have a real impact on end users
• Build, test and deploy your code to production - working closely with and learning from our excellent team of software engineers
• Communicate what is possible with data science and machine learning within your team and to the wider business
• Conduct pure exploratory research around novel problems and cutting edge techniques
• Having a real business impact in an organisation where data and data science is foundational to the business model and end product

Requirements

Key Skills

There are many indications that some people only apply to roles when they meet all the qualifications for a role. We believe that ticking off a list of skills is not the only thing that makes a great applicant. Therefore, the key requirement for this job is simply that you have experience leveraging big data to find patterns and make predictions. We’ll be particularly excited if you’ve deployed predictive models into production and have experience of time series modelling or search.

If that's you, then we encourage you to get in touch!

Benefits

Culture & Perks

At Qubit we believe that culture has to be nurtured. Our engineering team is constantly iterating on how we build software to create an environment that is supportive, friendly and driven. We encourage activities such as cross-functional pairing so that everyone has the opportunity to learn both technical skills and problem solving techniques. We promote engineers having direct customer exposure so that everyone has a shared interest in product discovery, and we regularly experiment with new ways of working.

We champion diversity and are proud to be an equal opportunity employer. We embrace difference with open arms and see it as a huge benefit to our community. We are dedicated to equal opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. If you have a disability or need that requires accommodation, please let us know.

• Generous equity options
• Excellent private health and dental insurance packages
• A subscription to the wellness platform Heka - https://www.hekahappy.com/
• A relaxed culture around time off and working from home (although we are all remote for now!)
• Top of the range macbook pro
• Subsidised gym membership
• Thank Qubit It’s Friday – we have lots of creative ways to let off steam at the end of the week
• Per-employee budget for training and development
• A subscription to the learning platform Learnerbly - https://www.learnerbly.com/
• Pension scheme with contribution matching
• Paid parental leave
• Dedicated time for charity/community work via Pledge 1% - https://pledge1percent.org
• Company over-performance bonuses